def forward_features()

in deepseek_vl2/models/siglip_vit.py [0:0]

• 14 lines of code
• 5 McCabe index (conditional complexity)

    def forward_features(self, x: torch.Tensor) -> torch.Tensor:
        if getattr(self, "is_first_stage", True):
            x = self.patch_embed(x)
            x = self._pos_embed(x)
            x = self.patch_drop(x)
            x = self.norm_pre(x)
        if self.grad_checkpointing and not torch.jit.is_scripting():
            skip_last = max(1, len(self.blocks) - self.num_recomputing_layers)
            x = checkpoint_seq(self.blocks, x, skip_last=skip_last)
        else:
            x = self.blocks(x)
        if getattr(self, "is_last_stage", True):
            x = self.norm(x)
        return x